Fanbo Xiang

Orcid: 0009-0005-5335-873X

According to our database1, Fanbo Xiang authored at least 18 papers between 2020 and 2024.

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Bibliography

2024
General-Purpose Sim2Real Protocol for Learning Contact-Rich Manipulation With Marker-Based Visuotactile Sensors.
IEEE Trans. Robotics, 2024

ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI.
CoRR, 2024

Point-SAM: Promptable 3D Segmentation Model for Point Clouds.
CoRR, 2024

2023
Part-Guided 3D RL for Sim2Real Articulated Object Manipulation.
IEEE Robotics Autom. Lett., November, 2023

Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation.
IEEE Trans. Robotics, June, 2023

Robo360: A 3D Omnispective Multi-Material Robotic Manipulation Dataset.
CoRR, 2023

FG-NeRF: Flow-GAN based Probabilistic Neural Radiance Field for Independence-Assumption-Free Uncertainty Estimation.
CoRR, 2023

NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Support.
CoRR, 2023

ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
OCRTOC: A Cloud-Based Competition and Benchmark for Robotic Grasping and Manipulation.
IEEE Robotics Autom. Lett., 2022

Close the Visual Domain Gap by Physics-Grounded Active Stereovision Depth Sensor Simulation.
CoRR, 2022

2021
ManiSkill: Learning-from-Demonstrations Benchmark for Generalizable Manipulation Skills.
CoRR, 2021

OCRTOC: A Cloud-Based Competition and Benchmark for Robotic Grasping and Manipulation.
CoRR, 2021

ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereo.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

NeuTex: Neural Texture Mapping for Volumetric Neural Rendering.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
SAPIEN: A SimulAted Part-Based Interactive ENvironment.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020


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